MCP Is Growing Up
Ask AI to Choose a prompt Write a TLDR of this post Explain the security risk Summarize what CISOs should know.
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Bring Your AI. Give It Reach. | Reach Security
Point an AI model at a security stack it doesn't fully understand and you get confident, wrong answers faster. Reach gives your AI a source of truth for security controls. The MCP Server connects MCP-compatible AI tools directly to Reach. The Public API brings Reach findings and evidence into SIEM, ticketing, and GRC workflows. The MCP Server is intentionally read-only, so your team decides when recommendations become actions.
How the Arctic Wolf Agentic SOC Delivers Faster, More Accurate Security Outcomes
Learn how Arctic Wolf Superintelligence Platform and the Swarm of Experts work together to deliver faster, more accurate outcomes for customers by leveraging unmatched telemetry, deterministic models, our golden data set and human expertise.
Treat Your AI Agents Like Humans or You Are Creating Risk
AI agents are about to act as humans inside your organization. Curtis Koenig, Head of Application Security at Gen, explains why treating them with the same identity and data controls is the single most important step to get ahead of AI risk. "We're going to give these agents the capability to do things as though they were humans. If we are not treating them like we treat our other human users in our organizations, that's where we're creating risk.".
If AI Can Build the Exploit, It Can Write the Patch
The window between an exploit being discovered and actively used is around eight hours. Curtis Koenig, Head of Application Security at Gen, explains why zero trust and a prepared incident response process remain the foundation for security teams navigating this new threat landscape. "The good news is that if the tool can find a vulnerability and create an exploit, it can find a vulnerability and write a patch as well.".
AI: The Catalyst for the Transmutation of IT and OT
Part 3 of the Enterprise OIT Series By Bill Moore, Founder & CEO, Xona Systems TL;DR -- Intelligence vs.
Which AI Signals Carry a Finding and Which Only Size It
A correlation rule joins several telemetry sources and fires when they agree. Guidance on writing them concentrates on thresholds, ordering and tuning for noise. The decision that determines whether a rule works is upstream of all of that. Each source in a rule plays one of three roles, and treating them interchangeably is what produces a rule that misses real events or fires on ones nobody can act on.
Jev's Paradox: The hidden cost of cheap AI decisions
This article was first published on LinkedIn. Consider a cybersecurity alert for a potentially malicious PowerShell script that downloads and runs a file. An AI agent in a security operations center (SOC) can handle it by picking from a fixed set of actions: close the alert as benign, collect more evidence, or send it to an analyst. Before letting the agent act on such alerts, the SOC needs to know how often it picks correctly and whether its confidence helps identify its mistakes.
Gen's Curtis Koenig on treating AI agents like human users to prevent security failures
Your backlog of low and medium severity vulnerabilities just became a real threat. AI can now chain them into critical exploits, and the window between exploit discovery and active use is around eight hours. Curtis Koenig, Head of Application Security at Gen, joins the show to explain why treating AI agents like human users is the single most important step security teams can take this year. CHAPTERS.
Generative AI Security: Are Your Developers Pasting Secrets Into LLMs?
This is the fifth post in our "Bring Your Own Source" series. The previous ones covered n8n workflow integration, Salesforce, GitLab CI, and GitHub Gists.